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LogiTorch: A PyTorch-based library for logical reasoning on natural language

Abstract

Logical reasoning on natural language is one of the most challenging tasks for deep learning models. There has been an increasing interest in developing new benchmarks to evaluate the reasoning capabilities of language models such as BERT. In parallel, new models based on transformers have emerged to achieve ever better performance on these datasets. However, there is currently no library for logical reasoning that includes such benchmarks and models. This paper introduces LogiTorch, a PyTorch-based library that includes different logical reasoning benchmarks, different models, as well as utility functions such as co-reference resolution. This makes it easy to directly use the preprocessed datasets, to run the models, or to finetune them with different hyperparameters. LogiTorch is open source and can be found on GitHub .
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Dates and versions

hal-03870592 , version 1 (24-11-2022)

Identifiers

  • HAL Id : hal-03870592 , version 1

Cite

Chadi Helwe, Chloé Clavel, Fabian Suchanek. LogiTorch: A PyTorch-based library for logical reasoning on natural language. The 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, Dec 2022, Abu Dhabi, United Arab Emirates. ⟨hal-03870592⟩
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